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Influence of surface water on coarse resolution C-band backscatter: Implications for freeze/thaw retrieval from scatterometer data.

Authors :
Bergstedt, Helena
Bartsch, Annett
Duguay, Claude R.
Jones, Benjamin M.
Source :
Remote Sensing of Environment. Sep2020, Vol. 247, pN.PAG-N.PAG. 1p.
Publication Year :
2020

Abstract

The freeze/thaw state of permafrost landscapes is an essential variable for monitoring ecological, hydrological and climate processes. Ground surface state can be obtained from satellite data through time series analysis of C-band backscatter from scatterometer and Synthetic Aperture Radar (SAR) observations. Scatterometer data has been used in a variety of studies concerning freeze/thaw retrieval of the land surface. Coarse spatial resolution scatterometer data has great potential for application in this field due to its high temporal resolution (approx. daily observations). In this study, we investigate the influence of sub-grid cell (12.5 km) surface water (ice free and ice covered) on freeze/thaw retrieval based on ASCAT data using a threshold algorithm. We found discrepancies related to the surface water fraction in the detected timing of thawing and freezing of up to 2 days earlier thawing for spring and 3.5 days earlier freezing for autumn for open water fractions of 40% resulting in an overestimation of the frozen season. Results of this study led to the creation of a method for correction of water fraction impact on freeze/thaw data. Additionally, this study demonstrates the applicability of a new approach to freeze/thaw retrieval which has not so far been tested for SAR, specifically Sentinel-1. • Influence of sub-grid cell surface water on freeze/thaw retrieval based on ASCAT data • Discrepancies related to the surface water fraction in the detected timing of thawing and freezing • Found a general overestimation of the frozen season. • Study demonstrates applicability of approach which was so far not tested for SAR. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00344257
Volume :
247
Database :
Academic Search Index
Journal :
Remote Sensing of Environment
Publication Type :
Academic Journal
Accession number :
144459972
Full Text :
https://doi.org/10.1016/j.rse.2020.111911